SAMPLING DISTRIBUTION- It is important to recognize that sample statistic itself a random sample. Sampling distribution of sample statistic is a probability distribution of all possible sample statistics computed from a set of equal size samples that were drawn randomly from the same population.For example- Suppose a random sample of 100 bonds are selected form population of major municipal bonds consist of 1000 bonds and the mean return of 100 sample bonds are calculated.Repeat this process many times will result in different estimates of population mean return one from each sample)Distribution of these estimates of mean is sampling distribution of meanSAMPLING DISTRIBUTION IS DISTINCT FROM THE DISTRIBUTION OF ACTUAL PRICE OF 1000 BODS In An Underlying POPULATION And WILL HAVE DIFFERENT PARAMETERSMY QUESTIONWHAT DOES THIS SENTENCE MEANS?/SAMPLING DISTRIBUTION IS DISTINCT FROM THE DISTRIBUTION OF ACTUAL PRICE OF 1000 BODS In An Underlying POPULATION And WILL HAVE DIFFERENT PARAMETERSSource of questionSchweser CFA LEVEL 1 SAMPLING AND ESTIMATIONPAGE 282 BOOK1

Hi, answer to your question is that since the sample is taken out from the population so every time a new sample is selected randomly from the population the sampling distribution will be different from the actual population or actual price of 1000 bonds in this example. Also, sampling distribution have different parameters from population underlying. parameters are for example sample mean so it will always be distinct from population (maybe close to population but not exactly the same).

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